Artificial Neural Network Applications for Software Reliability Prediction

Nonfiction, Computers, Programming, Software Development
Cover of the book Artificial Neural Network Applications for Software Reliability Prediction by Manjubala Bisi, Neeraj Kumar Goyal, Wiley
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Author: Manjubala Bisi, Neeraj Kumar Goyal ISBN: 9781119223924
Publisher: Wiley Publication: September 18, 2017
Imprint: Wiley-Scrivener Language: English
Author: Manjubala Bisi, Neeraj Kumar Goyal
ISBN: 9781119223924
Publisher: Wiley
Publication: September 18, 2017
Imprint: Wiley-Scrivener
Language: English

Artificial neural network (ANN) has proven to be a universal approximator for any non-linear continuous function with arbitrary accuracy. This book presents how to apply ANN to measure various software reliability indicators: number of failures in a given time, time between successive failures, fault-prone modules and development efforts. The application of machine learning algorithm i.e. artificial neural networks application in software reliability prediction during testing phase as well as early phases of software development process is presented as well. Applications of artificial neural network for the above purposes are discussed with experimental results in this book so that practitioners can easily use ANN models for predicting software reliability indicators.

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Artificial neural network (ANN) has proven to be a universal approximator for any non-linear continuous function with arbitrary accuracy. This book presents how to apply ANN to measure various software reliability indicators: number of failures in a given time, time between successive failures, fault-prone modules and development efforts. The application of machine learning algorithm i.e. artificial neural networks application in software reliability prediction during testing phase as well as early phases of software development process is presented as well. Applications of artificial neural network for the above purposes are discussed with experimental results in this book so that practitioners can easily use ANN models for predicting software reliability indicators.

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